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https://github.com/bytedance/deer-flow.git
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feat: asyncio-native Actor framework with supervision, middleware, and pluggable mailbox
Lightweight actor library built on asyncio primitives (~800 lines): - Actor base class with lifecycle hooks (on_started/on_stopped/on_restart) - ActorRef with tell (fire-and-forget) and ask (request-response) - Supervision: OneForOne/AllForOne strategies with restart limits - Middleware pipeline for cross-cutting concerns - Pluggable Mailbox interface (MemoryMailbox default, RedisMailbox optional) - ReplyRegistry + ReplyChannel: ask() works across any mailbox backend - System-level thread pool for blocking I/O (run_in_executor) - Dead letter handling, poison message quarantine, parallel shutdown - 22 tests + benchmark suite
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greatmengqi
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"""Actor framework benchmarks — throughput, latency, concurrency."""
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import asyncio
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import time
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import statistics
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from deerflow.actor import Actor, ActorSystem, Middleware
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class NoopActor(Actor):
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async def on_receive(self, message):
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return message
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class CounterActor(Actor):
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async def on_started(self):
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self.count = 0
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async def on_receive(self, message):
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self.count += 1
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return self.count
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class ChainActor(Actor):
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"""Forwards message to next actor in chain."""
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next_ref = None
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async def on_receive(self, message):
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if self.next_ref is not None:
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return await self.next_ref.ask(message)
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return message
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class ComputeActor(Actor):
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"""Simulates CPU work via thread pool."""
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async def on_receive(self, message):
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def fib(n):
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a, b = 0, 1
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for _ in range(n):
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a, b = b, a + b
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return a
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return await self.context.run_in_executor(fib, message)
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class CountMiddleware(Middleware):
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def __init__(self):
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self.count = 0
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async def on_receive(self, ctx, message, next_fn):
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self.count += 1
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return await next_fn(ctx, message)
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def fmt(n):
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if n >= 1_000_000:
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return f"{n/1_000_000:.1f}M"
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if n >= 1_000:
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return f"{n/1_000:.0f}K"
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return str(n)
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async def bench_tell_throughput(n=100_000):
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"""Measure tell (fire-and-forget) throughput."""
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system = ActorSystem("bench")
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ref = await system.spawn(CounterActor, "counter", mailbox_size=n + 10)
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start = time.perf_counter()
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for _ in range(n):
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await ref.tell("inc")
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# Wait for all messages to be processed
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count = await ref.ask("get", timeout=30.0)
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elapsed = time.perf_counter() - start
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await system.shutdown()
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rate = n / elapsed
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print(f" tell throughput: {fmt(n)} msgs in {elapsed:.2f}s = {fmt(int(rate))}/s")
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async def bench_ask_throughput(n=50_000):
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"""Measure ask (request-response) throughput."""
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system = ActorSystem("bench")
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ref = await system.spawn(NoopActor, "echo")
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start = time.perf_counter()
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for _ in range(n):
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await ref.ask("ping")
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elapsed = time.perf_counter() - start
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await system.shutdown()
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rate = n / elapsed
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print(f" ask throughput: {fmt(n)} msgs in {elapsed:.2f}s = {fmt(int(rate))}/s")
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async def bench_ask_latency(n=10_000):
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"""Measure ask round-trip latency percentiles."""
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system = ActorSystem("bench")
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ref = await system.spawn(NoopActor, "echo")
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# Warmup
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for _ in range(100):
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await ref.ask("warmup")
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latencies = []
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for _ in range(n):
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t0 = time.perf_counter()
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await ref.ask("ping")
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latencies.append((time.perf_counter() - t0) * 1_000_000) # microseconds
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await system.shutdown()
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latencies.sort()
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p50 = latencies[len(latencies) // 2]
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p99 = latencies[int(len(latencies) * 0.99)]
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p999 = latencies[int(len(latencies) * 0.999)]
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print(f" ask latency: p50={p50:.0f}µs p99={p99:.0f}µs p99.9={p999:.0f}µs")
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async def bench_concurrent_actors(num_actors=1000, msgs_per_actor=100):
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"""Measure throughput with many concurrent actors."""
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system = ActorSystem("bench")
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refs = []
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for i in range(num_actors):
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refs.append(await system.spawn(CounterActor, f"a{i}", mailbox_size=msgs_per_actor + 10))
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start = time.perf_counter()
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async def send_batch(ref, n):
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for i in range(n):
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await ref.tell("inc")
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# Yield control every 50 msgs so actor loops can drain
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if i % 50 == 49:
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await asyncio.sleep(0)
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return await ref.ask("get", timeout=30.0)
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results = await asyncio.gather(*[send_batch(r, msgs_per_actor) for r in refs])
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elapsed = time.perf_counter() - start
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total = num_actors * msgs_per_actor
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delivered = sum(results)
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rate = total / elapsed
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loss = total - delivered
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print(f" {num_actors} actors × {msgs_per_actor} msgs: {fmt(total)} in {elapsed:.2f}s = {fmt(int(rate))}/s (loss: {loss})")
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await system.shutdown()
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async def bench_actor_chain(depth=100):
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"""Measure ask latency through a chain of actors (hop overhead)."""
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system = ActorSystem("bench")
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refs = []
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for i in range(depth):
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refs.append(await system.spawn(ChainActor, f"c{i}"))
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# Link chain: c0 → c1 → ... → c99
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for i in range(depth - 1):
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refs[i]._cell.actor.next_ref = refs[i + 1]
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start = time.perf_counter()
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result = await refs[0].ask("ping", timeout=30.0)
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elapsed = time.perf_counter() - start
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assert result == "ping"
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per_hop = elapsed / depth * 1_000_000 # µs
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print(f" chain {depth} hops: {elapsed*1000:.1f}ms total, {per_hop:.0f}µs/hop")
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await system.shutdown()
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async def bench_middleware_overhead(n=50_000):
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"""Measure overhead of middleware pipeline."""
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mw = CountMiddleware()
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system_plain = ActorSystem("plain")
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ref_plain = await system_plain.spawn(NoopActor, "echo")
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system_mw = ActorSystem("mw")
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ref_mw = await system_mw.spawn(NoopActor, "echo", middlewares=[mw])
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# Plain
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t0 = time.perf_counter()
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for _ in range(n):
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await ref_plain.ask("p")
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plain_elapsed = time.perf_counter() - t0
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# With middleware
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t0 = time.perf_counter()
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for _ in range(n):
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await ref_mw.ask("p")
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mw_elapsed = time.perf_counter() - t0
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overhead = ((mw_elapsed - plain_elapsed) / plain_elapsed) * 100
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print(f" middleware overhead: {overhead:+.1f}% ({fmt(n)} ask calls, 1 middleware)")
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await system_plain.shutdown()
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await system_mw.shutdown()
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async def bench_executor_parallel(num_tasks=16):
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"""Measure thread pool parallelism with CPU work."""
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system = ActorSystem("bench", executor_workers=8)
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refs = [await system.spawn(ComputeActor, f"cpu{i}") for i in range(num_tasks)]
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start = time.perf_counter()
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results = await asyncio.gather(*[r.ask(10_000, timeout=30.0) for r in refs])
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elapsed = time.perf_counter() - start
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print(f" executor parallel: {num_tasks} fib(10K) in {elapsed*1000:.0f}ms ({num_tasks/elapsed:.0f} tasks/s)")
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await system.shutdown()
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async def bench_spawn_teardown(n=5000):
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"""Measure actor spawn + shutdown speed."""
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system = ActorSystem("bench")
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start = time.perf_counter()
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refs = []
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for i in range(n):
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refs.append(await system.spawn(NoopActor, f"a{i}"))
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spawn_elapsed = time.perf_counter() - start
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start = time.perf_counter()
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await system.shutdown()
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shutdown_elapsed = time.perf_counter() - start
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print(f" spawn {n}: {spawn_elapsed*1000:.0f}ms ({n/spawn_elapsed:.0f}/s)")
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print(f" shutdown {n}: {shutdown_elapsed*1000:.0f}ms")
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async def main():
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print("=" * 60)
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print(" Actor Framework Benchmarks")
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print("=" * 60)
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print()
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print("[Throughput]")
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await bench_tell_throughput()
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await bench_ask_throughput()
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print()
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print("[Latency]")
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await bench_ask_latency()
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await bench_actor_chain()
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print()
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print("[Concurrency]")
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await bench_concurrent_actors()
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await bench_executor_parallel()
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print()
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print("[Overhead]")
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await bench_middleware_overhead()
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print()
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print("[Lifecycle]")
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await bench_spawn_teardown()
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print()
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print("=" * 60)
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print(" Done")
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print("=" * 60)
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if __name__ == "__main__":
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asyncio.run(main())
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